Integrated, observation-based carbon monitoring for wooded ecosystems

Approach: In a statistical framework known as GNN (Gradient Nearest Neighbor modeling), we create maps of forest condition by combining time-series Landsat Thematic Mapper (TM) data with plot data from the Forest Inventory and Analysis (FIA) program. We will then use high-quality estimates of biomass mapped at fine scales using laser imaging (lidar) to determine the reliability of our maps.

Attribution of change: Follow this link to learn more about how we make maps estimating what caused a given kind of forest change.

Science and management questions:

How much have forest carbon pools or fluxes been affected by natural processes (insects, fire, wind, growth) versus anthropogenic processes (harvest, land-use change)? Are the relative impacts of those processes constant or changing as policy and climate also change?

How have those processes of change been distributed across forest types, ownerships, management approaches, and policy periods?

Has forest management intended to reduce susceptibility to insect and fire actually reduced vulnerability of carbon pools to unplanned loss a regional scale?

Deliverables

These science questions will be addressed by analysis of a set of key deliverables. These include annual, 30m resolution maps in Washington, Oregon, and California of: